10^th March 2015 – John, a senior merchandiser in a large Asian fashion retailer, Shoe Inc., is struggling to correlate multiple spreadsheets with footwear samples kept on his desk. Along with his colleagues, Sasha and Maria, he’s facing a deadline for planning the “Winter 2015” assortment.

Their current focus is on the “Heels” category, and the Three Musketeers are having difficulty identifying and incorporating current trends as well as insights from last season.

These trends and insights are part of the understanding necessary to answer key questions essential for achieving their stock turn targets: What depth they should put in for various colour ways of a given style? How do they ensure that they don’t miss out on multibagger designs in their trendiest colours? What insights can they gather from the piles of data and tonnes of physical samples and product pictures around them?

The challenge they face is that the spreadsheet data has a bunch of SKU codes and unless they are correlated with actual images the quality of insights will be seriously limited.

Recognizing this, Sasha, the resident techno-geek came up with a spread sheet and pasted in product pictures in each row. This was much better than dealing with the physical piles but only produced a static view of what was selling well. Moreover, re-creating the spreadsheet for every new item was painfully time-consuming. Apart from the drudgery involved, insights were limited to one shoe at a time while perspectives of how collections are performing were missing.

John, was concerned about the low productivity and poor insights generated from this process. He runs into Mark, the CEO of Shoe Inc. at lunch and apprises him of the situation. Mark recollects a recent meeting he had with a friend regarding Kanvas – and suggests John to try it. Mark believes that Kanvas can help solve this issue and get Shoe Inc. closer to its goal of 2 to 3 percent stock turn increase every alternate quarter.

15^th March 2015 – John calls in the Kanvas team to conduct a demo session for his design and merchandising teams. He also invites Mark. It becomes apparent within 10 minutes that Kanvas’ ability to seamlessly integrate images and data into actionable insights can solve the problem John is facing. Wanting to see beyond the demo data, Mark requests the Kanvas team to stay back and provide analysis using data from Shoe Inc. Kanvas team could easily upload data and images and a demonstration is done within an hour, immediately showcasing new insights.

The swift analysis helped identify that the 80 percent of this year’s top sellers in the Heels category comprised of block heels compared to only 30 percent last year.

Moreover, basic shades were selling twice as compared to the bright shades. Mark is quick to point out the possibility of a brand image transition from style driven to comfort driven.

John suggested that customer preferences might have changed drastically. Both agreed to increase allocation of block heels immediately to cater to the growing demand. Such analysis could not be done before as Shoe Inc.’s product specifications could not be included as attributes. Even if they could have been included, it was virtually impossible to process all the tabular data simultaneously in the human brain and come up with insights. Visual analysis of images allowed them to spot trends which may were hiding like a lost city in the vast sands of spread sheets’ granular data.

15^th June 2015 – Kanvas has become a core part of the process flow for both merchandising and design teams. In addition to churning out automated image reports every week on what’s working and what’s not, all line reviews and assortment planning are also being conducted through Kanvas. John, Sasha and Maria were much happier and much more productive.

Mark is also expecting a further 1 to 2 percent increase in stock turn by managing store level inventories through Kanvas and pushing products similar to those popular sellers hitting early stock outs.

15^th July 2015 – Mark is moving closer to his business goals of better margins through improved stock turnovers. He is not only confident of meeting his stock turn target but is shooting to get an extra 2 percent.